提出了一种改进的基于KKT 条件的增量学习算法。

Presents an improved incremental learning algorithm based on KKT conditions.

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基于原训练样本集和新增训练样本集在增量训练中地位等同，提出了一种新的SVM增量学习算法。

Based on the equivalence between the original training set and the newly added training set, a new algorithm for SVM-based incremental learning was proposed.

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为了将一般增量学习算法扩展到并行计算环境中，提出一种基于多支持向量机分类器的增量学习算法。

In order to extend common incremental learning algorithms into a parallel computation setting, an incremental learning algorithm with multiple support vector machine classifiers is proposed.

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